A typical method of insuring fields are ready for an operation, such as a fertilizer application, after a rain event involves people driving around in vehicles to physically scout the fields of interest. Such an approach is labor intensive and can be inaccurate because of the quality of observations made from the road. For example, the surface of the field may be dry, but still very wet underneath. Also, parts of the field, particularly low spots, may not be visible from the road. Thus, equipment and material may be dispatched to fields that are not ready for field work. In one such scenario, a fertilizer applicator operator then may be faced with a decision of applying fertilizer with damage to the field or else sending the fertilizer to a storage location for later application and then moving to another field which is hopefully in better condition.
Some soil moisture models provide an opportunity to automatically predict regions that are ready for an operation. One example is the IBIS model currently available from the University of Wisconsin at Madison at the WEB address: http://gaim.unh.edu/Structure/Intercomparison/EMDI/models/ibis.html, http://www.sage.wisc.edu/download/IBIS/ibis.html.
IBIS is a regional scale crop and soil moisture model that can be run at 1 square kilometer (km) resolution. At that resolution, for example, a fertilizer dealer trade area of 25,000 square kilometers would have 25,000 “cells” in its computer simulation and run in a timely fashion. However, many fields are in the 0.25-0.50 square kilometer (km) size, and the 1 square kilometer resolution is not good enough to assess field conditions for some field operations, such as fertilizer application.
Field level soil simulators such as PALMS are currently available from the University of Wisconsin at Madison at the WEB address: (http://www.warf.ws/technologies.jsp?techfield=Environment&msnum=510&casecod e=P04428US), and operate with cell sizes of 5 meters by 5 meters (5 m×5 m, or roughly the operating width of many farm machines.
The 5 m linear dimension is 1/200 the 1 km dimension. Thus, a single 1 km by 1 km cell in IBIS would contain 200 by 200 or 40,000 PALMS cells. This is an n^2 computational time growth rate due to increased resolution and ignores any computational time growth from the model algorithms as a function of number of cells. To highlight the significance of this execution time growth rate, suppose the IBIS model would provide an output for the 25,000 square kilometer trade area in 1 hour at 1 square kilometer resolution. It would then take 40,000 hours to get a result at the 5 m*5 m resolution or over 4½ years of continuous execution. This is clearly too long to impact today's field activities in light of a recent rain event, such as last night's rain.